The trend of artificial intelligence is rising all around us. The development of modern technologies, the presence of a mini computing device (smartphones) in everyone's hands, and the ability to make concrete deductions from vast amounts of data generated by the constant flow of information, definitely show the prevalence of AI in our daily lives.
The earliest example of AI in modern computing can be traced back to Alan Turing when he solved the Nazi`s Enigma Code in World War II and set forth an altogether different way of thinking for technologists. It is because of him that concepts such as Big Data, Machine Learning, and Deep Learning have become commonplace today.
AI in The Financial World
The two biggest financial meltdowns in the last century were, one, after World War II and the second, during the housing bubble or the SubPrime Crisis. These events raised questions for policymakers around the globe about whether the Financial Institutions had the capability to mitigate these risks or understand the changes or events that were leading to such crises.
If one observes carefully, the way AI or machine learning are employed has significantly changed after the 2008 financial crisis. There is already a system in place that works on algorithms; the way you spend your money automatically aligns you to different offers. For instance, a digital wallet system now automatically gives different users different kinds of post-paid limits. If you sign up for such a service, who decides these limits? Are there banking personnel sitting at Paytm`s office with a long ledger, allocating different limits after looking at different documents? Of course not. It is decided by a pre-fed algorithm that takes into account various information about the individual and then allocates the limits.
What is the Need for AI in Finance?
Finance is a vast industry that encompasses everything from capital generation to capital markets and GDP to individual account books. What all these concepts have in common, is an enormous amount of data. When a human brain tries to gather information from these data sets, it can do so by taking a limited number of factors in mind. But with the help of machine learning, which is essentially a self-improving algorithm, the possibilities become countless and so do the outcomes.
Role of AI in Lending
Lending is the core function of the banking industry and for a long time, there have been two schools of thought when it comes to the use of AI in Banking and Finance. Lending functions have always had reservations. The question is, will these reservations or biases get resolved with the application of AI in Finance ?
The question poses a valid point. However, from a broader perspective, we can easily say that yes, there are some reservations when it comes to lending functions and they will remain, whether we use AI in Finance or not. Having said that, it holds true that using AI will definitely add to the function of lending. With time, surely, there will be a mechanism developed by the regulators themselves to help erase these biases. A sure thing with applying AI in the Finance Industry is an improvement in speed and accuracy with which the lending functions were performed earlier.
One of the major factors influencing the disbursement of consumer loans today is the use of the credit rating system. Though an efficient tool, credit rating is computed by using algorithms that are dictated by variables and their interpretation by AI. This may at times leave room for bias depending on the weightage given to individual factors. Thus, elimination of such biased credit decision data will result in a smoother functioning of the AI based Financial Analysis and credit rating tools
Is There Any Hard Evidence of How AI Can Help?
AI is used in every industry, including lending, be it credit card lending, EMI facilities or a sudden pop-up offering No-cost EMI while abandoning an online shopping cart. But to a person with some financial knowledge, these facts do not cross the mark where it can be regarded as evidence for how effective AI is in lending functions.
Let us consider a recent example:
Kabbage is a data and technology company that serves its customers by provision of access to automated yet simplified and flexible lines of credit. Small businesses having little or no credit histories can feed their digital footprints into Kabbage and are provided with funding options within a relatively smaller time frame without any hassles.
This efficacy has led them to generate more than $16 Billions of working capital for as many as 500,000 small businesses, the PayCheck Protection Program included.
Kabbage customers gained access to nearly $3 billion in working capital loans in 2019, driven by around 60,000 new customers. In just 4 months, they delivered more than double the amount of funding ($7 billion) to roughly five times the number of new customers (297,000), with an average loan size of $23,000 and a median loan size of $12,700.
To quote Anthony Sabelli, Kabbage, "Amazon Textract" helped support 80% of Kabbage`s PPP applicants to receive a fully automated lending experience and reduced approval times from multiple days to a median speed of four hours.American Express has now acquired Kabbage.
Do we have such a Unicorn in India?
Shriram Finance Limited is a company that strives to achieve excellence and is driven to achieve success using its core values and ensuring the use of the latest technology available in the industry.
Shriram Finance Limited has been in the industry since 1986. As one of the major players in the retail financing space, they are categorised as the largest financiers of MSMEs and two-wheelers in India. The company also encompasses various types of loans that comprise home loans, passenger vehicle loans and other commercial vehicles Loans. Shriram Group also has personal loan offers against gold and gold ornaments.
Shriram Group, a company that has 43 glorious years of existence in India, has a very keen focus on the latest technology and has always been ahead of the curve when it comes to technological advancement. The group has specialized teams that focus on Digital Transition and Artificial Intelligence aspects for the company.
Being highly customer-focussed, the company takes pride in making the customer experience remarkable. While there always remains the hurdle of existing credit bias in getting any type of loans, Shriram group is overcoming this hurdle of customer dissatisfaction through the use of Artificial Intelligence and Machine learning methods to obtain a pre-sanction for various loans.
A similar success story is that of the insurance teams of the group, where the calculations of risks are based on modern algorithms and the turn-around time for deposit handling or life insurance is exceptional.
The initiatives of the company and actual delivery on their platform tell tales of efficiency and efficacy that were previously unheard in this sector. Shriram Group can be regarded as the unicorn when it comes to the Indian lending space using digital technology and modern Artificial Intelligence.
But does this answer the original question - AI resolution in lending: hype or reality?
With companies like the Shriram Group at the helm of AI developments in the Finance Sector, application of AI in Finance may turn out to be a reality, which will very soon be observed as a common practice in the financial dealings of the public in general.
